J. Wiart

activity

20192023

(0, m, s)

-nets, and negative covariance: applying symbolic computation to quasi-Monte Carlo integration

7 citations · 8 across the 5 of their papers we have counts for

collaborators

Showing 2020Show all

3 papers · 1 filter

math.ST2020

On the distribution of scrambled $(0, m, s)$ -nets over unanchored boxes

C. Lemieux, J. Wiart

We introduce a new quality measure to assess randomized low-discrepancy point sets of finite size $n$ . This new quality measure, which we call "pairwise sampling dependence index",…

math.CO2020

Improved dispersion bounds for modified Fibonacci lattices

Ralph Kritzinger, Jaspar Wiart

We study the dispersion of point sets in the unit square; i.e. the size of the largest axes-parallel box amidst such point sets. It is known that $\liminf_{N\to\infty} N\mathrm{dis…

math.NA2020★ 7 cited

Walsh functions, scrambled $(0, m, s)$ -nets, and negative covariance: applying symbolic computation to quasi-Monte Carlo integration

Jaspar Wiart, Elaine Wong

We investigate base $b$ Walsh functions for which the variance of the integral estimator based on a scrambled $(0, m, s)$ -net in base $b$ is less than or equal to that of the Monte-C…

On the distribution of scrambled (0,m,s)-nets over unanchored boxes

Improved dispersion bounds for modified Fibonacci lattices

Walsh functions, scrambled (0,m,s)-nets, and negative covariance: applying symbolic computation to quasi-Monte Carlo integration

On the distribution of scrambled $(0, m, s)$ -nets over unanchored boxes

Walsh functions, scrambled $(0, m, s)$ -nets, and negative covariance: applying symbolic computation to quasi-Monte Carlo integration